| Title | Plan of work |
|---|---|
| Intern Name | Karalyn Ostler |
| Sponsor Name | David Christensen, Seattle Public Library |
| Date | 06.24.2019 |
ODL intern Karalyn Ostler will help the project sponsor, Seattle Public Library (SPL), identify, extract and transform lesser-used relevant external open data into actionable intelligence for frontline staff. Karalyn will start with assessing the data needs of frontline staff at SPL through interviews with regional managers, asking what information about the community would help them better plan future services. From the information gathered, Karalyn will identify open datasets from open data sources, like the City of Seattle Open Data portal and State of Washington open data portal, and internal datasets available from SPL that can be used to address these data needs. Using Python or R and other data visualization software, Karalyn will transform the datasets into more useful and easier to understand objects, including but not limited to graphs, maps, and written reports. This process will be thoroughly documented so that future projects can build off of this work. Stakeholders served include SPL, SPL frontline staff, and the general public that they serve.
What is this project supposed to achieve, and why?
- Assess data needs of SPL frontline staff: Karalyn will communicate with 2 SPL regional managers to assess their data needs. Specifically, she will ask them what information about the local community would be most helpful for them to make better informed decisions about SPL services. The gathered information from staff will be used in this project to find open datasets and create useful materials for the frontline staff to easily use in their planning process.
- Identify relevant open datasets related to Seattle and SPL: Karalyn will search through several open data repositories with Seattle data to find datasets with relevant information about the local community that can be combined with existing internal datasets. This project aims to leverage already existing datasets about the local community that have been posted by credible sources and make the information from these datasets more useful for library staff.
- Create materials using selected datasets for use by SPL staff: Many open datasets are stored in forms that are easily machine readable but can be hard for humans to understand. Karalyn will transform and synthesize selected open datasets into visualizations and reports for use by frontline staff. This project aims to create a comprehensive description of relevant elements of the community that connect to SPL services. By better understanding the community, the hope is that SPL frontline staff can make more informed decisions and create better services that fit the needs of the community.
Due to time constraints, only a select number of SPL staff data needs will be addressed. If more time allows, more datasets could be transformed so that a wider range of staff needs can be met.
What will this project produce? This should include items like reports, best practices, software, data, metadata schemas, models or figures, and documentation. See the two types of deliverables below:
- Weekly documentation in GitHub and two public blog posts, as required by the ODL internship guidelines. These will also serve as updates to David Christensen at SPL.
- Assessment report of SPL frontline staff data needs. This includes responses from staff about what they want to know about the local community in relation to SPL services.
- List of open datasets that relate to possible data needs of SPL staff.
- Code notebooks with visualizations and data transformations.
- Written summaries of findings from datasets.
- Presentations and reports of findings for SPL frontline staff.
- Final written report outlining all information found from datasets, including graphs, figure, and reports.
- Public presentation of internship work on August 16, 2019, as required by ODL internship guidelines.
- All documentation and code will be uploaded to GitHub and any other platform as determined by sponsor.
- Free and open source software and file formats will be prioritized for data analysis to ensure future continued access to code and datasets.
- Code will be thoroughly documented with comments and markdown so that code is easily understandable and reusable by others in the future.
- All information found through data transformation will be documented in a written report in addition to a visual/verbal presentation for relevant staff.
Create a general timeline for completing each of the deliverables that you listed above. After you have settled on a timeline with feedback from your mentor, you should enter these as Milestones in GitHub's Issues tracker. Each task that you perform or plan to perform can then be files as an issue that is attached to a specific milestone.
- Create interview question sheet/script.
By Jun 27DONE - Contact 2 regional managers and conduct 30-minute interviews about information needs.
By Jul 5DONE - From data needs communicated in interviews, identify community and environmental factors that might have related open datasets. By Jul 9
- Create list of open datasets about Seattle and surrounding community from open data sources based on information from staff. By Jul 12
- Check quality of datasets. By Jul 16
- Look through available internal SPL datasets and identify relevant By Jul 17
- Select external and internal datasets for further analysis. By Jul 19
- Import and clean/tidy datasets. By Jul 24
- Look for ways to combine multiple datasets about community for richer content. By Jul 30
- Run statistical analysis where applicable. By Aug 7
- Create figures and graphs where applicable. By Aug 7
- Cleanup code notebook and make sure documentation is included where necessary. By Aug 9
- Write reports with findings for regional managers and frontline staff. By Aug 13
- Create and present findings to regional managers and frontline staff. By Aug 16
- Present findings to Southeast Region librarians. Sept 24
- Post first blog post on Medium. By Jul 12
- Post second blog post on Medium. By Aug 9
- Finalize full report of all findings to give to sponsor. By Aug 15
- Prepare and present at ODL Showcase event. By Aug 16
- 06.17.19 - First draft of plan completed.
- 06.24.19 - Second draft with updates based on feedback from ODL team, David Christensen, and Jay Lyman.
- 07.03.19 - Update small details and dates.
- Update the ODL GitHub repository at least weekly and more as needed, so the internship’s documentation is current and thorough. Notify David and others as needed about updated reports.
- Respond to SPL staff or ODL team within 24 business hours.
- Use email, Slack, and phone as needed for communication with SPL staff and the ODL team.
- Meet with ODL Team weekly to check-in.
- Karalyn will visit SPL Central Library and other branches as needed by sponsor and other participating SPL staff.